Why is in silico drug design significant?

A large number of novel structures of protein targets are becoming available through crystallography, NMR and bioinformatics methods, thereby increasing the demand for the use of computational tools that can identify and analyze active sites and suggest potential drug molecules that can bind specifically to these sites. Time and cost required for designing a new drug are exorbitantly high and at an unacceptable level. Intervention of computers at plausible steps is imperative in bringing down the cost and time required for the drug discovery process.

The use of computers and computational methods permeates all aspects of drug discovery today, and forms the core of structure-based drug design. High-performance computing, data management software and internet are facilitating the access of huge amount of data generated and transforming the massive complex biological data into workable knowledge in modern drug discovery research.

Services offered:

Protein Crystal Structure Determination
- Data collection of single crystals or powders of drug molecules
- Data collection of protein crystals and protein-ligand co-crystals
- Structure Determination
- Crystal Structure Refinement
- Crystal Image Annotation
- Structure Annotation
- Ligand Binding Evaluation

Allesh Biosciences Labs offers in silico technologies and services to augment lab-based research so as to accelerate discovery and minimize expenses. AlleshBio leverages on computational chemistry and chemogenomics approaches in identifying potential novel targets and “personalized” targets. Virtual high throughput screening (vHTS) and in silico ADME/Toxicity prediction models being used in identification and obtention of hits and lead molecules.

Computer-Aided Drug Design (CADD)
Drug targets are typically key molecules involved in a specific metabolic or cell signaling pathway that is known, or believed, to be related to a particular disease state. Drug targets are most often proteins and enzymes in these pathways. Drug compounds are designed to inhibit, restore or otherwise modify the structure and behavior of disease-related proteins and enzymes. CADD uses the known 3D geometrical shape or structure of proteins to assist in the development of new drug compounds.

The capabilities include, but not limited to:

Computational Chemistry: Structure-Based Design
- Virtual high throughput screening by docking or pharmacophore design
- QM/MM methods for rigorous assessment of key protein-ligand interactions
- MD methods to analyze protein conformational changes
- Free energy simulations for improved binding affinity models

Computational Chemistry: Ligand-Based Design
- Scaffold hopping
- QM calculations for QSAR, ligand conformation determination and energy profiling
- QSAR and pharmacophore based predictive models for ligand optimization

Chemoinformatics
- Identification of novel IP space on small organic molecules
- Virtual library design of synthetically tractable compounds
- Small Organic Molecule Library Enumeration
- Similarity and diversity analysis methods
- Property filtration and analysis

Chemogenomics
- Protein-target identification and druggability assessment
- Target hopping and scaffold morphing
- Annotation of disease-relevant targets
- Using chemogenomic database in virtual screening

Bioinformatics
- Protein family analysis
- Protein homology modeling
- Active site identification and comparison
- Sequence Analysis

Other Core Technologies
- In silico screening/docking of ligands
- Prediction of binding modes
- In silico ADME/Tox property prediction
- Establishing quantitative structure-activity relationship (QSAR)
- Establishing quantitative structure-property relationship (QSPR)
- Receptor-based and ligand-based pharmacophore design
- Fragment-based drug design
- Design of focused, diverse and thematic chemistry libraries
- Lead optimization & de-novo drug design
- Calculation of physico-chemical properties
- Biological and physico-chemical predictive model building
- Synthetic organic reaction modeling
- Study on short-lived intermediates and transition states
- Biosimulations